10/16/2018

Background

Reliably count zebra mussels at low density

Existing designs for mussel surveys

  • Timed search: discovery at very low density
  • Quadrat survey: useful for high-densities

Benefits of using a more formal survey design

  • Control the amount of area surveyed
    • Determine uncertainty in density
  • This means we can make comparisons across space and time

Distance sampling

An approach for low and intermediate densities

Lake survey: summer 2017

Distance and detectability

Estimated detection function

The payoff

\({\color{red} X}\): is the number of zebra mussels detected

\(\color{blue} A\): is the amount of are surveyed

\(\color{orange} P\): is the detection probability of detecting a zebra mussel (\(P = 0.60\))

  • Observed density: \(\frac{\color{red}X}{\color{blue}A} = 0.08\)

  • Estimated density: \(\frac{\color{red}X}{\color{orange}P\,\color{blue}A} = 0.25\) (SE =\(0.09)\)

Investigating survey tradeoffs

The fast/slow tradeoff

Should we go fast and cover lots of area, but maybe miss some mussels?

or

Should we go slow and detect everything, but cover less area?

Controlling effort through design

Lake surveys: summer 2018

Time budget approach

  • Time to setup each transect
  • Time to conduct each survey
  • Time to move between transects

Time to perform transect setup & search

Time it takes to move between transects

Number of transects that can be completed

Impacts of the time budget on estimates

Conclusions

Acknowledgements

Naomi Blinick

Leslie Schroeder

Sarah Baker

Aislyn Keyes

Austin Hilding

Thomas Ostendorf

Kylie Cattoor

Keegan Lund

John Fieberg

Michael McCartney

Steve McComas

Rich Rezanka

Tom Jones